Senior Annotation & Quality Manager

Career Area:

Technology, Digital and Data

Job Description:

Your Work Shapes the World at Caterpillar Inc.

When you join Caterpillar, you're joining a global team who cares not just about the work we do – but also about each other.  We are the makers, problem solvers, and future world builders who are creating stronger, more sustainable communities. We don't just talk about progress and innovation here – we make it happen, with our customers, where we work and live. Together, we are building a better world, so we can all enjoy living in it.

Help Build the Future of Caterpillar. 

At Caterpillar, technology always has a purpose, which is to solve our customers’ toughest challenges. Through Cat Technology, we are solving problems by building the intelligence layer that connects machines, data, and people to make jobsites safer, more productive, and more sustainable. By combining deep domain expertise in physical systems with software, connectivity, autonomy, and AI, we deliver solutions that work in the real world—on real jobsites, on a global scale. 

You’ll build and deploy against one of the most unique data foundations—over 1.6 million connected assets generating real-world data daily.  These data and platform capabilities are enabling the development of AI models, edge computing architectures, and software systems that scale across fleets, products, and industries. The result will be a new generation of machines that continuously learn, improve, and deliver performance at scale.

Be Part of What’s Next in Autonomous Construction Sites

Construction autonomy is one of the most complex challenges in applied AI, and at Caterpillar, advancements in physical AI, simulation, sensing, and edge computing are turning things that once felt impossible—intelligent machines operating in dynamic jobsites—into reality. 

Our connected ecosystem brings together massive volumes of high-quality data to create a foundation where engineers like you can build and deploy against. 

If this work motivates you, we invite you to join our team. In these roles, you’ll work at the intersection of the physical and digital worlds. You’ll help design and deliver intelligent systems that enable machines to perceive their environment, make informed decisions, and support safer, more productive operations. 

Apply today to build the new era of construction autonomy at Caterpillar.

Role:

We are seeking a Data Annotations & Quality Manager to lead the teams responsible for producing, automating, and validating the datasets that power Physical AI, autonomy, robotics, and machine learning systems.

This leader will oversee three critical functions:

• Data Annotation – Teams responsible for manual labeling and quality assurance of multimodal sensor data.
• AI Automation Engineering – Engineers who build and maintain auto-labeling, AI-assisted annotation, and human-in-the-loop systems to improve scalability and efficiency.
• Data Quality Engineering – Engineers responsible for measuring, monitoring, and enforcing data quality standards across the data lake to ensure datasets remain fit for AI training and production use.

The successful candidate will build and lead a high-performing organization that transforms raw sensor and operational data into trusted, high-quality datasets that enable machine learning, simulation, digital twin, and autonomy initiatives. This role requires a combination of people leadership, operational excellence, data-centric AI expertise, and quality engineering discipline.

What You Will Do

Lead Data Annotation Operations

• Manage teams responsible for labeling image, video, LiDAR, radar, telemetry, geospatial, and other machine-generated data.
• Establish scalable annotation processes, standards, and quality controls.
• Own annotation throughput, quality, cost, and delivery metrics.
• Drive continuous improvement of annotation workflows, instructions, and quality assurance practices.
• Partners with AI and software engineering teams align annotation priorities with model development needs.

Lead AI-Powered Annotation Automation

• Build and lead teams developing auto-labeling, pre-labeling, active learning, and human-in-the-loop annotation solutions.
• Drive adoption of AI-assisted labeling tools to improve annotation speed and reduce costs.
• Establish strategies for maximizing automation while maintaining quality and trustworthiness.
• Define success metrics for automation effectiveness, precision, recall, and reviewer effort reduction.
• Collaborate with machine learning teams to incorporate model feedback into annotation workflows.

Lead Data Quality Engineering<